{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "0b9ffbb2-8d33-eb0c-5a42-0733bdc3b74b",
    "_uuid": "e14f65723f5ac826104e861c45e58525740d8b2a"
   },
   "source": [
    "# Bikeshare数据集上的数据探索\n",
    "\n",
    "1、\t任务描述\n",
    "请在Capital Bikeshare （美国Washington, D.C.的一个共享单车公司）提供的自行车数据上进行回归分析。根据每天的天气信息，预测该天的单车共享骑行量。\n",
    "\n",
    "原始数据集地址：http://archive.ics.uci.edu/ml/datasets/Bike+Sharing+Dataset\n",
    "1)\t文件说明\n",
    "day.csv: 按天计的单车共享次数（作业只需使用该文件）\n",
    "hour.csv: 按小时计的单车共享次数（无需理会）\n",
    "readme：数据说明文件\n",
    "\n",
    "2)\t字段说明\n",
    "Instant记录号\n",
    "Dteday：日期\n",
    "Season：季节（1=春天、2=夏天、3=秋天、4=冬天）\n",
    "yr：年份，(0: 2011, 1:2012)\n",
    "mnth：月份( 1 to 12)\n",
    "hr：小时 (0 to 23)  （只在hour.csv有，作业忽略此字段）\n",
    "holiday：是否是节假日\n",
    "weekday：星期中的哪天，取值为0～6\n",
    "workingday：是否工作日\n",
    "1=工作日 （是否为工作日，1为工作日，0为非周末或节假日\n",
    "weathersit：天气（1：晴天，多云 ",
    "2：雾天，阴天 ",
    "3：小雪，小雨 ",
    "4：大雨，大雪，大雾）\n",
    "temp：气温摄氏度\n",
    "atemp：体感温度\n",
    "hum：湿度\n",
    "windspeed：风速\n",
    "casual：非注册用户个数\n",
    "registered：注册用户个数\n",
    "cnt：给定日期（天）时间（每小时）总租车人数，响应变量y （cnt = casual + registered）\n",
    "\n",
    "casual、registered和cnt三个特征均为要预测的y，作业里只需对cnt进行预测"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 导入必要的工具包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "_cell_guid": "2ba3154a-c2aa-3158-1984-63ad2c0c786a",
    "_uuid": "5eb696b95780825e94ddb49787f9fa339fc3833b"
   },
   "outputs": [],
   "source": [
    "# 数据读取及基本处理\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# plotting\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sn\n",
    "\n",
    "# setting params\n",
    "params = {'legend.fontsize': 'x-large',\n",
    "          'figure.figsize': (30,10),\n",
    "          'axes.labelsize': 'x-large',\n",
    "          'axes.titlesize':'x-large',\n",
    "          'xtick.labelsize':'x-large',\n",
    "          'ytick.labelsize':'x-large',}\n",
    "\n",
    "sn.set_style('whitegrid')\n",
    "sn.set_context('talk')\n",
    "\n",
    "plt.rcParams.update(params)\n",
    "pd.options.display.max_colwidth = 600\n",
    "\n",
    "# pandas display data frames as tables\n",
    "from IPython.display import display, HTML"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 读入数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "_cell_guid": "21fa35be-878b-b4f2-ef6e-68dc070b8bfa",
    "_uuid": "73aee228226be55c0c8a6e4fcbf818c56cd94926"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>dteday</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.344167</td>\n",
       "      <td>0.363625</td>\n",
       "      <td>0.805833</td>\n",
       "      <td>0.160446</td>\n",
       "      <td>331</td>\n",
       "      <td>654</td>\n",
       "      <td>985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.363478</td>\n",
       "      <td>0.353739</td>\n",
       "      <td>0.696087</td>\n",
       "      <td>0.248539</td>\n",
       "      <td>131</td>\n",
       "      <td>670</td>\n",
       "      <td>801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.196364</td>\n",
       "      <td>0.189405</td>\n",
       "      <td>0.437273</td>\n",
       "      <td>0.248309</td>\n",
       "      <td>120</td>\n",
       "      <td>1229</td>\n",
       "      <td>1349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2011-01-04</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.212122</td>\n",
       "      <td>0.590435</td>\n",
       "      <td>0.160296</td>\n",
       "      <td>108</td>\n",
       "      <td>1454</td>\n",
       "      <td>1562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2011-01-05</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.226957</td>\n",
       "      <td>0.229270</td>\n",
       "      <td>0.436957</td>\n",
       "      <td>0.186900</td>\n",
       "      <td>82</td>\n",
       "      <td>1518</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   instant      dteday  season  yr  mnth  holiday  weekday  workingday  \\\n",
       "0        1  2011-01-01       1   0     1        0        6           0   \n",
       "1        2  2011-01-02       1   0     1        0        0           0   \n",
       "2        3  2011-01-03       1   0     1        0        1           1   \n",
       "3        4  2011-01-04       1   0     1        0        2           1   \n",
       "4        5  2011-01-05       1   0     1        0        3           1   \n",
       "\n",
       "   weathersit      temp     atemp       hum  windspeed  casual  registered  \\\n",
       "0           2  0.344167  0.363625  0.805833   0.160446     331         654   \n",
       "1           2  0.363478  0.353739  0.696087   0.248539     131         670   \n",
       "2           1  0.196364  0.189405  0.437273   0.248309     120        1229   \n",
       "3           1  0.200000  0.212122  0.590435   0.160296     108        1454   \n",
       "4           1  0.226957  0.229270  0.436957   0.186900      82        1518   \n",
       "\n",
       "    cnt  \n",
       "0   985  \n",
       "1   801  \n",
       "2  1349  \n",
       "3  1562  \n",
       "4  1600  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 读入数据\n",
    "train = pd.read_csv(\"day.csv\")\n",
    "train.head()\n",
    "#print(\"train : \" + str(train.shape))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 731 entries, 0 to 730\n",
      "Data columns (total 16 columns):\n",
      "instant       731 non-null int64\n",
      "dteday        731 non-null object\n",
      "season        731 non-null int64\n",
      "yr            731 non-null int64\n",
      "mnth          731 non-null int64\n",
      "holiday       731 non-null int64\n",
      "weekday       731 non-null int64\n",
      "workingday    731 non-null int64\n",
      "weathersit    731 non-null int64\n",
      "temp          731 non-null float64\n",
      "atemp         731 non-null float64\n",
      "hum           731 non-null float64\n",
      "windspeed     731 non-null float64\n",
      "casual        731 non-null int64\n",
      "registered    731 non-null int64\n",
      "cnt           731 non-null int64\n",
      "dtypes: float64(4), int64(11), object(1)\n",
      "memory usage: 91.5+ KB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "没有缺失数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "be11c1c7-acfe-cb9a-bc81-95d461b884c5",
    "_uuid": "b53750ea6a3a2a02aa4297f5401e29c2f4d92e31"
   },
   "source": [
    "## 数据探索"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>2.496580</td>\n",
       "      <td>0.500684</td>\n",
       "      <td>6.519836</td>\n",
       "      <td>0.028728</td>\n",
       "      <td>2.997264</td>\n",
       "      <td>0.683995</td>\n",
       "      <td>1.395349</td>\n",
       "      <td>0.495385</td>\n",
       "      <td>0.474354</td>\n",
       "      <td>0.627894</td>\n",
       "      <td>0.190486</td>\n",
       "      <td>848.176471</td>\n",
       "      <td>3656.172367</td>\n",
       "      <td>4504.348837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>211.165812</td>\n",
       "      <td>1.110807</td>\n",
       "      <td>0.500342</td>\n",
       "      <td>3.451913</td>\n",
       "      <td>0.167155</td>\n",
       "      <td>2.004787</td>\n",
       "      <td>0.465233</td>\n",
       "      <td>0.544894</td>\n",
       "      <td>0.183051</td>\n",
       "      <td>0.162961</td>\n",
       "      <td>0.142429</td>\n",
       "      <td>0.077498</td>\n",
       "      <td>686.622488</td>\n",
       "      <td>1560.256377</td>\n",
       "      <td>1937.211452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.059130</td>\n",
       "      <td>0.079070</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022392</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>22.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>183.500000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.337083</td>\n",
       "      <td>0.337842</td>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.134950</td>\n",
       "      <td>315.500000</td>\n",
       "      <td>2497.000000</td>\n",
       "      <td>3152.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.498333</td>\n",
       "      <td>0.486733</td>\n",
       "      <td>0.626667</td>\n",
       "      <td>0.180975</td>\n",
       "      <td>713.000000</td>\n",
       "      <td>3662.000000</td>\n",
       "      <td>4548.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>548.500000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.655417</td>\n",
       "      <td>0.608602</td>\n",
       "      <td>0.730209</td>\n",
       "      <td>0.233214</td>\n",
       "      <td>1096.000000</td>\n",
       "      <td>4776.500000</td>\n",
       "      <td>5956.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>731.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.861667</td>\n",
       "      <td>0.840896</td>\n",
       "      <td>0.972500</td>\n",
       "      <td>0.507463</td>\n",
       "      <td>3410.000000</td>\n",
       "      <td>6946.000000</td>\n",
       "      <td>8714.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          instant      season          yr        mnth     holiday     weekday  \\\n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean   366.000000    2.496580    0.500684    6.519836    0.028728    2.997264   \n",
       "std    211.165812    1.110807    0.500342    3.451913    0.167155    2.004787   \n",
       "min      1.000000    1.000000    0.000000    1.000000    0.000000    0.000000   \n",
       "25%    183.500000    2.000000    0.000000    4.000000    0.000000    1.000000   \n",
       "50%    366.000000    3.000000    1.000000    7.000000    0.000000    3.000000   \n",
       "75%    548.500000    3.000000    1.000000   10.000000    0.000000    5.000000   \n",
       "max    731.000000    4.000000    1.000000   12.000000    1.000000    6.000000   \n",
       "\n",
       "       workingday  weathersit        temp       atemp         hum   windspeed  \\\n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean     0.683995    1.395349    0.495385    0.474354    0.627894    0.190486   \n",
       "std      0.465233    0.544894    0.183051    0.162961    0.142429    0.077498   \n",
       "min      0.000000    1.000000    0.059130    0.079070    0.000000    0.022392   \n",
       "25%      0.000000    1.000000    0.337083    0.337842    0.520000    0.134950   \n",
       "50%      1.000000    1.000000    0.498333    0.486733    0.626667    0.180975   \n",
       "75%      1.000000    2.000000    0.655417    0.608602    0.730209    0.233214   \n",
       "max      1.000000    3.000000    0.861667    0.840896    0.972500    0.507463   \n",
       "\n",
       "            casual   registered          cnt  \n",
       "count   731.000000   731.000000   731.000000  \n",
       "mean    848.176471  3656.172367  4504.348837  \n",
       "std     686.622488  1560.256377  1937.211452  \n",
       "min       2.000000    20.000000    22.000000  \n",
       "25%     315.500000  2497.000000  3152.000000  \n",
       "50%     713.000000  3662.000000  4548.000000  \n",
       "75%    1096.000000  4776.500000  5956.000000  \n",
       "max    3410.000000  6946.000000  8714.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#对数据值型特征，用常用统计量观察其分布\n",
    "train.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. 离散特征的分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "season属性的不同取值和出现的次数\n",
      "3    188\n",
      "2    184\n",
      "1    181\n",
      "4    178\n",
      "Name: season, dtype: int64\n",
      "\n",
      "mnth属性的不同取值和出现的次数\n",
      "12    62\n",
      "10    62\n",
      "8     62\n",
      "7     62\n",
      "5     62\n",
      "3     62\n",
      "1     62\n",
      "11    60\n",
      "9     60\n",
      "6     60\n",
      "4     60\n",
      "2     57\n",
      "Name: mnth, dtype: int64\n",
      "\n",
      "weathersit属性的不同取值和出现的次数\n",
      "1    463\n",
      "2    247\n",
      "3     21\n",
      "Name: weathersit, dtype: int64\n",
      "\n",
      "weekday属性的不同取值和出现的次数\n",
      "6    105\n",
      "1    105\n",
      "0    105\n",
      "5    104\n",
      "4    104\n",
      "3    104\n",
      "2    104\n",
      "Name: weekday, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "#对类别型特征，观察其取值范围及直方图\n",
    "categorical_features = ['season','mnth','weathersit','weekday']\n",
    "for col in categorical_features:\n",
    "    print('\\n%s属性的不同取值和出现的次数'%col)\n",
    "    print(train[col].value_counts())\n",
    "    train[col] = train[col].astype('object')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "类别型特征的取值不多\n",
    "类别型特征可以采用独热编码（One hot encoding）/哑编码"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. 数值特征的分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#对数值型特征，直方图\n",
    "numerical_features = ['temp','atemp','hum','windspeed']\n",
    "train[numerical_features].hist()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. 特征与目标之间的关系"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.1 每年骑行量的分布\n",
    "violinplot中用x表示类别（年）信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x214c7b5dda0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.violinplot(data=train[['yr',\n",
    "                        'cnt']],\n",
    "              x=\"yr\",y=\"cnt\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2011年和2012年的分布差异很大"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.2 一年中每天的骑车量\n",
    "用颜色参数hue表示类别（年）信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5,1,'dayly distribution of counts')]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import datetime\n",
    "\n",
    "train['date'] = pd.to_datetime(train['dteday'])\n",
    "train['dayofyear'] = train[\"date\"].dt.dayofyear  #减今年的第几天\n",
    "\n",
    "fig,ax = plt.subplots()\n",
    "sn.pointplot(data=train[['dayofyear',\n",
    "                           'cnt',\n",
    "                           'yr']],\n",
    "             x='dayofyear',y='cnt',\n",
    "             hue='yr',ax=ax)\n",
    "ax.set(title=\"dayly distribution of counts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "每年开始和结束的数量少，中间多，骑行量和季节/月份有关"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.3 季节与骑车数量的关系\n",
    "violinplot得到详细分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x214c5a55400>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.violinplot(data=train[['season',\n",
    "                        'cnt']],\n",
    "              x=\"season\",y=\"cnt\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "能看出来每个季节骑行量的分布不同\n",
    "barplot利用矩阵条的高度反映数值变量的集中趋势，以及使用errorbar功能（差棒图）来估计变量之间的差值统计。\n",
    "谨记barplot展示的是某种变量分布的平均值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5,1,'Seasonly distribution of counts')]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "sn.barplot(data=train[['season',\n",
    "                       'cnt']],\n",
    "           x=\"season\",y=\"cnt\")\n",
    "ax.set(title=\"Seasonly distribution of counts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "骑行量和季节的关系就很明显了：第2、3、4季度的骑行量明显高于第1季度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.4 月份与骑车数量的关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5,1,'Monthly distribution of counts')]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "sn.barplot(data=train[['mnth',\n",
    "                       'cnt']],\n",
    "           x=\"mnth\",y=\"cnt\")\n",
    "ax.set(title=\"Monthly distribution of counts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.5 天气和骑车数目的关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5,1,'weathersit distribution of counts')]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "sn.barplot(data=train[['weathersit',\n",
    "                       'cnt']],\n",
    "           x=\"weathersit\",y=\"cnt\")\n",
    "ax.set(title=\"weathersit distribution of counts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.6 工作日和节假日的分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x214c8879358>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,(ax1,ax2) = plt.subplots(ncols=2)\n",
    "sn.barplot(data=train,x='holiday',y='cnt',ax=ax1)\n",
    "sn.barplot(data=train,x='workingday',y='cnt',ax=ax2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.7 数值型特征和y之间的相关性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x214c88ee518>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "corrMatt = train[[\"temp\",\"atemp\",\n",
    "                  \"hum\",\"windspeed\",\n",
    "                  \"casual\",\"registered\",\n",
    "                  \"cnt\"]].corr()\n",
    "mask = np.array(corrMatt)\n",
    "mask[np.tril_indices_from(mask)] = False\n",
    "sn.heatmap(corrMatt, mask=mask,\n",
    "           vmax=.8, square=True,annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "体感温度和温度高度相关\n",
    "目标cnt与温度正相关、湿度和风速负相关"
   ]
  }
 ],
 "metadata": {
  "_change_revision": 0,
  "_is_fork": false,
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
